Automatic Speech Recognition
Transformers
Safetensors
Chinese
English
voxtral_realtime
realtime
turn-taking
speech-recognition
voice-assistant
endpointing
barge-in
Instructions to use x-square-robot/X2-Turn-4B-0812 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use x-square-robot/X2-Turn-4B-0812 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="x-square-robot/X2-Turn-4B-0812")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("x-square-robot/X2-Turn-4B-0812") model = AutoModelForMultimodalLM.from_pretrained("x-square-robot/X2-Turn-4B-0812", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 384 Bytes
2d3b544 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"feature_extractor": {
"feature_extractor_type": "VoxtralRealtimeFeatureExtractor",
"feature_size": 128,
"global_log_mel_max": 1.5,
"hop_length": 160,
"n_fft": 400,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000,
"win_length": 400
},
"processor_class": "VoxtralRealtimeProcessor"
}
|